🎆Optimal Path Rewards

In our design, the optimal path refers to selecting the path that best meets target requirements, has the highest efficiency, or lowest cost from multiple possible solutions through specific evaluation criteria and optimization algorithms. In large- scale complex systems, especially multi-level Large Language Model (LLM) combinations, the selection of optimal paths is particularly important as it directly affects system performance, resource utilization, and response speed. In building and optimizing multi-level LLM combination systems, we use components like LLM Planner and Optimal Path Evaluator to automatically combine multiple LLMs into a hierarchical tree structure, and automatically explore optimal combination paths through training and fine-tuning. The Optimal Path Evaluator is responsible for evaluating and optimizing multiple combination paths generated by the LLM Planner. Through the collaborative work of these two components, the LLM system forms a hierarchical tree structure that both clearly defines the division of responsibilities among LLM levels and provides good scalability and maintainability for the system. The optimal path is like a world record in the AI world, with each breakthrough representing a major innovation.